The Cell Software team is looking for a Data Engineer to support automation of reports and actions for the 4680 Cell Program. This includes automation of production reporting, defect prediction, advanced statistics, maintaining data pipelines/databases, and creating live visualization tools to enable the 4680 team for excellence.

• Analyze manufacturing, equipment and product field data and extract useful statistics and insights about failures to drive meaningful improvements to production quality and customer experience
• Work effectively with Engineers and conduct end-to-end analyses, from data requirement gathering, to data processing and modeling
• Monitor key manufacturing metrics, understanding root causes of changes
• Interpret data, analyze results using statistical techniques and provide ongoing reports
• Identify, analyze, and interpret trends or patterns in complex data sets and depict the story via dashboards and reports
• Maintain existing data visualizations, data pipelines and dashboard enhancement requests
• Acquire data from primary or secondary data sources and maintain databases/data systems to empower operational and exploratory analysis
• Dive deep into investigations of potential system issues, using data to arrive at logical conclusions and to convince the team what action is necessary
• Perform data quality validations to ensure data creation is as per the business needs and expectations

• Degree in Management Information Systems, Computer Science, Math, Physics, Mechanical Engineering, Electrical Engineering, Statistics or equivalent experience
• 2 years of experience writing scripts or programs with Python OR Go-Lang
• 2 years of experience with SQL database queries
• 2 year of experience building analytical dashboards
• 1 year of experience with Git
• Knowledge of various data communication protocols (e.g. REST API, WebSocket)
• Able to work under pressure while collaborating and managing competing demands with tight deadlines
• Strong verbal and written communication skills to quickly translate needs into data analysis problems and effectively communicate learnings